Modifying messages to be more discoverable on a social network

ABSTRACT

A method, system and computer program product for improving the discoverability of messages on a social network. The creation of a proposed message that requests a response from a target audience is detected. The social network is then searched to identify search terms and posts related to the proposed message. Upon identifying the search terms, the search terms are ranked in order of usage among the identified posts. A list of identified search terms in order of rank is then presented to the user to modify the proposed message. The proposed message is modified using a search term selected by the user from the list of search terms. The modified message is then posted on the social network. In this manner, the message created by the user has been modified to improve the discoverability of the message on the social network and to increase responses from an appropriate target audience.

TECHNICAL FIELD

The present invention relates generally to social media communications,and more particularly to modifying messages to be more discoverable on asocial network.

BACKGROUND

There are many different ways to share and process information amongusers, such as via social media posts. For example, a user may post amessage on the user's social network profile space, such as a wall, oron an activity stream (e.g., news feed, timeline). Such a mechanismallows users to rapidly share information with others as well as rapidlygather information from others.

However, such messages may not necessarily be distributed to theappropriate or intended group. For example, messages may only be postedfor the sole purpose in hopes of eliciting a response withoutconsidering the aspect of the message being discovered by theappropriate or the intended group. Consequently, the author of themessage may not receive many responses, if at all, from his/her messagedue to the lack of discoverability of the message.

SUMMARY

In one embodiment of the present invention, a computer-implementedmethod for improving discoverability of messages on a social networkcomprises detecting a creation of a proposed message that requests aresponse from a target audience, where the proposed message comprisesone or more words. The method further comprises searching the socialnetwork to identify search terms and posts related to the proposedmessage. The method additionally comprises ranking the identified searchterms in order of usage among the identified posts. Furthermore, themethod comprises presenting a list of ranked search terms to a user tosubstitute at least one word of the one or more words in the proposedmessage. Additionally, the method comprises modifying the proposedmessage by replacing the at least one word with a respective search termfrom the list of ranked search terms in response to the user selectingthe respective search term. In addition, the method comprises postingthe modified proposed message on the social network.

Other forms of the embodiment of the method described above are in asystem and in a computer program product.

The foregoing has outlined rather generally the features and technicaladvantages of one or more embodiments of the present invention in orderthat the detailed description of the present invention that follows maybe better understood. Additional features and advantages of the presentinvention will be described hereinafter which may form the subject ofthe claims of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the present invention can be obtained when thefollowing detailed description is considered in conjunction with thefollowing drawings, in which:

FIG. 1 illustrates a social network system configured in accordance withan embodiment of the present invention;

FIG. 2 illustrates a hardware configuration of a message analyzerconfigured in accordance with an embodiment of the present invention;

FIGS. 3A-3B are a flowchart of a method for improving thediscoverability of a message on a social network where the message doesnot include a mention or hashtag in accordance with an embodiment of thepresent invention; and

FIG. 4 is a flowchart of a method for improving the discoverability of amessage on a social network where the message includes a hashtag ormention in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention comprises a method, system and computer programproduct for improving the discoverability of messages on a socialnetwork. In one embodiment of the present invention, the creation of aproposed message that requests a response from a target audience isdetected. The social network is then searched to identify search termsand posts related to the proposed message. For example, natural languageprocessing may be utilized to search the social network to identifysearch terms (e.g., “McCarron traded”) and posts related to the proposedmessage (e.g., “Starting QB Team traded. What are your thoughts?”). Uponidentifying the search terms, the search terms are ranked in order ofusage among the identified posts. A list of identified search terms inorder of rank is then presented to the user to modify the proposedmessage. The proposed message is modified using a search term from thelist of identified search terms that was selected by the user. Themodified message is then posted on the social network. In this manner,the message created by the user has been modified to improve thediscoverability of the message on the social network and to increaseresponses from an appropriate target audience by including terms thatare more likely to catch the attention of intended recipients,especially if such search terms are currently trending.

In the following description, numerous specific details are set forth toprovide a thorough understanding of the present invention. However, itwill be apparent to those skilled in the art that the present inventionmay be practiced without such specific details. In other instances,well-known circuits have been shown in block diagram form in order notto obscure the present invention in unnecessary detail. For the mostpart, details considering timing considerations and the like have beenomitted inasmuch as such details are not necessary to obtain a completeunderstanding of the present invention and are within the skills ofpersons of ordinary skill in the relevant art.

Referring now to the Figures in detail, FIG. 1 illustrates a socialnetwork system 100 configured in accordance with an embodiment of thepresent invention. Referring to FIG. 1, social network system 100includes a community of users using client devices 101A-101C (identifiedas “Client Device A,” “Client Device B,” and “Client Device C,”respectively, in FIG. 1) to be involved in social network system 100.Client devices 101A-101C may collectively or individually be referred toas client devices 101 or client device 101, respectively. It is notedthat both computing devices 101 and the users of computing devices 101may be identified with element number 101. Client device 101 may be aportable computing unit, a Personal Digital Assistant (PDA), asmartphone, a laptop computer, a mobile phone, a navigation device, agame console, a desktop computer system, a workstation, an Internetappliance and the like.

Client devices 101 may participate in a social network by communicating(by wire or wirelessly) over a network 102, which may be, for example, alocal area network, a wide area network, a wireless wide area network, acircuit-switched telephone network, a Global System for MobileCommunications (GSM) network, Wireless Application Protocol (WAP)network, a WiFi network, an IEEE 802.11 standards network, variouscombinations thereof, etc. Other networks, whose descriptions areomitted here for brevity, may also be used in conjunction with system100 of FIG. 1 without departing from the scope of the present invention.

System 100 further includes a social network server 103, which may be aweb server configured to offer a social networking and/or microbloggingservice, enabling users of client devices 101 to send and read otherusers' posts. “Posts,” as used herein, include any one or more of thefollowing: text (e.g., messages, comments, sub-comments and replies),audio, video images, etc. Social network server 103 is connected tonetwork 102 by wire or wirelessly. While FIG. 1 illustrates a singlesocial network server 103, it is noted for clarity that multiple serversmay be used to implement the social networking and/or microbloggingservice.

System 100 further includes what is referred to herein as the “messageanalyzer” 104 connected to network 102 by wire or wirelessly. Messageanalyzer 104 is configured to modify a message being created by a userof client device 101 in a manner that allows the message to be morediscoverable after it is posted on the social network as discussedfurther below. A description of the hardware configuration of messageanalyzer 104 is provided below in connection with FIG. 2.

System 100 is not to be limited in scope to any one particular networkarchitecture. System 100 may include any number of client devices 101,networks 102, social network servers 103 and message analyzers 104.Furthermore, in one embodiment, message analyzer 104 may be part ofclient device 101 or social network server 103.

Referring now to FIG. 2, FIG. 2 illustrates a hardware configuration ofmessage analyzer 104 (FIG. 1), which is representative of a hardwareenvironment for practicing the present invention. Referring to FIG. 2,message analyzer 104 has a processor 201 coupled to various othercomponents by system bus 202. An operating system 203 runs on processor201 and provides control and coordinates the functions of the variouscomponents of FIG. 2. An application 204 in accordance with theprinciples of the present invention runs in conjunction with operatingsystem 203 and provides calls to operating system 203 where the callsimplement the various functions or services to be performed byapplication 204. Application 204 may include, for example, a program forimproving the discoverability of a message on a social network asdiscussed further below in association with FIGS. 3A-3B and 4.

Referring again to FIG. 2, read-only memory (“ROM”) 205 is coupled tosystem bus 202 and includes a basic input/output system (“BIOS”) thatcontrols certain basic functions of message analyzer 104. Random accessmemory (“RAM”) 206 and disk adapter 207 are also coupled to system bus202. It should be noted that software components including operatingsystem 203 and application 204 may be loaded into RAM 206, which may bemessage analyzer's 104 main memory for execution. Disk adapter 207 maybe an integrated drive electronics (“IDE”) adapter that communicateswith a disk unit 208, e.g., disk drive. It is noted that the program forimproving the discoverability of a message on a social network asdiscussed further below in association with FIGS. 3A-3B and 4, mayreside in disk unit 208 or in application 204.

Message analyzer 104 may further include a communications adapter 209coupled to bus 202. Communications adapter 209 interconnects bus 202with an outside network (e.g., network 102 of FIG. 1) thereby allowingmessage analyzer 104 to communicate with client devices 101 and socialnetwork server 103.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

As stated in the Background section, there are many different ways toshare and process information among users, such as via social mediaposts. For example, a user may post a message on the user's socialnetwork profile space, such as a wall, or on an activity stream (e.g.,news feed, timeline). Such a mechanism allows users to rapidly shareinformation with others as well as rapidly gather information fromothers. However, such messages may not necessarily be distributed to theappropriate or intended group. For example, messages may only be postedfor the sole purpose in hopes of eliciting a response withoutconsidering the aspect of the message being discovered by theappropriate or the intended group. Consequently, the author of themessage may not receive many responses, if at all, from his/her messagedue to the lack of discoverability of the message.

The principles of the present invention provide a means for improvingthe discoverability of a message on a social network by the author'stargeted group as discussed below in connection with FIGS. 3A-3B and 4.FIGS. 3A-3B are a flowchart of a method for improving thediscoverability of a message on a social network where the message doesnot include a mention or hashtag. FIG. 4 is a flowchart of a method forimproving the discoverability of a message on a social network where themessage includes a mention or hashtag.

As stated above, FIGS. 3A-3B are a flowchart of a method 300 forimproving the discoverability of a message on a social network where themessage does not include a mention or hashtag in accordance with anembodiment of the present invention.

Referring now to FIG. 3A, in conjunction with FIGS. 1-2, in step 301, adetermination is made by message analyzer 104 as whether the creation ofa proposed message by user 101 is detected. In one embodiment, messageanalyzer 104 monitors the selection of an icon (e.g., message icon,tweet button) by user 101 indicating the intention of creating amessage. In another embodiment, message analyzer 104 monitors for textentered in a message box used for posting a message on a social network.In one embodiment, user 101 may indicate the creation of a message tomessage analyzer 104 via a user interface of computing device 101.

If message analyzer 104 has not detected the creation of a proposedmessage by user 101, then message analyzer 104 continues to monitor forthe creation of a proposed message by user 101 in step 301.

If, however, message analyzer 104 has detected the creation of aproposed message by user 101, then, in step 302, a determination is madeby message analyzer 104 as to whether the proposed message requests aresponse from a target audience.

In one embodiment, message analyzer 104 utilizes natural languageprocessing to determine whether the proposed message requests a responsefrom a target audience. For example, if user 101 uses a question mark inhis/her proposed message, then such a punctuation mark may indicate arequest for a response to the user's message. In another example,message analyzer 104 may utilize natural language processing to identifykeywords that signify a request for a response, such as “what” or“when.” For instance, user 101 may type the message “Starting QB Teamtraded. What are your thoughts?” In such a message, the keyword “what”and the punctuation mark of “?” may be used by message analyzer toconclude that the proposed message requests a response from a targetaudience.

In one embodiment, message analyzer 104 utilizes natural languageprocessing to determine the target audience of the proposed message. Forexample, in the proposed message of “Starting QB Team traded. What areyour thoughts?”, it may be inferred that the target audience involvesfans of football since the term “QB” is an abbreviation for thequarterback position in the game of football. Furthermore, messageanalyzer 104 may analyze the social profile of the user 101 who composedthe message to identify further information, such as favorite sportsteams. If user 101 indicated that he/she follows the Cincinnati Bengalsfootball team, then it may be inferred that user 101 is referring to thestarting quarterback of the Cincinnati Bengals football team, and hence,the target audience are fans of the Cincinnati Bengals football team.

In another embodiment, message analyzer 104 may also analyzer the socialprofiles of the user's friends, where the user's friends may beidentified on the user's social profile page (e.g., friend list). Suchfriends may be deemed to be a target audience.

In another embodiment, message analyzer 104 utilizes geolocation toidentify a target audience, such as a target audience that would beinclined to respond immediately. For example, user 101 may be located ata baseball game while he/she is creating the proposed message. Hence,the target audience may include those watching the same baseball game asuser 101, such as the friends of user 101 who have indicated they arewatching the same baseball game on their social profile.

In another embodiment, message analyzer 104 utilizes an identifiedcommunication medium (e.g., broadcast of baseball game on Internet andtelevision) to identify a target audience, such as a target audiencethat would be inclined to respond immediately. For example, user 101 maybe located at a baseball game while he/she is creating the proposedmessage. The baseball game may also be currently broadcasted. As aresult, the target audience may include those watching the baseball game(e.g., watching the game on their smartphone, watching the game on theirtelevision), including the user's friends who have indicated they arebaseball enthusiasts on their social profile page.

In one embodiment, only messages deemed to be of a certain importance,containing confidential information, containing a specific keyword(e.g., “why”) or based on paid/promoted offering, are modified toimprove the discoverability of the message as discussed below.

If the proposed message does not request a response from a targetaudience, then message analyzer 104 continues to monitor for thecreation of a proposed message by user 101 in step 301.

If, however, the proposed message requests a response from a targetaudience, then, in step 303, message analyzer 104 searches the socialnetwork to identify search terms and posts related to the proposedmessage. In one embodiment, such search terms are search terms used inmessages posted by the target audience determined in step 302 that arerelated to the proposed message. In one embodiment, the posts aremessages posted by the target audience determined in step 302.

In one embodiment, message analyzer 104 utilizes natural languageprocessing to identify search terms and posts related to the proposedmessage. For instance, referring to the above example, in the proposedmessage of “Starting QB Team traded. What are your thoughts?”, messageanalyzer 104 searches the social network to identify search terms andposts involving a Cincinnati Bengals quarterback being traded (orpossibly being traded). As previously discussed, it was determined bymessage analyzer 104 that the term “QB” referred to the quarterbackposition in football and that the quarterback referenced was probablythe quarterback that played for the Cincinnati Bengals since user 101 isa big fan of the Cincinnati Bengals football team. Furthermore, asdiscussed above, message analyzer 104 may have determined that thefollowers of the Cincinnati Bengals football team are the targetaudience. As a result, message analyzer 104 searches the social networkto identify search terms and posts from followers of the CincinnatiBengals football team involving a trade (rumor or actual) of thestarting quarterback of the Cincinnati Bengals football team.

For example, message analyzer 104 may identify the following searchterms used by the target audience: “McCarron traded,” and “McCarron newteam.” In a further example, message analyzer 104 may identify thefollowing post used by the target audience: “AJ McCarron traded toDallas—New QB.”

In one embodiment, message analyzer 104 only identifies search terms andposts that occurred within a window of time (e.g., last 24 hours). Inone embodiment, message analyzer 104 may only identifies search termsinvolving at least two terms. In one embodiment, message analyzer 104may limit the analysis to specific languages, minimum frequency andsocial recommendations.

In one embodiment, message analyzer 104 only identifies search terms andposts that are deemed to be most important or relevant to the targetaudience involving the proposed message. For example, message analyzer104 only identifies the search terms and posts that are deemed to bemost important or relevant to the target audience involving the topic ofthe proposed message. For instance, if the proposed message involved thehockey player Henrik Zetterberg, then, using natural languageprocessing, message analyzer 104 would identify search terms and postsdeemed to be most important or relevant to the target audience involvingthe proposed message, such as the health status of Henrik Zetterberg.Message analyzer 104 may determine that the health status is animportant topic to followers of the hockey player Henrik Zetterbergsince it involves the availability of Henrik Zetterberg playing the gameof hockey.

In one embodiment, message analyzer 104 may utilize synonyms,colloquialisms, antonyms, etc. of keywords identified in the proposedmessage when searching the social network in order to expand the set ofidentified search terms and posts related to the proposed message.Furthermore, message analyzer 104 may normalize subject/proper nounsinto the general subject to expand the set of identified search termsand posts related to the proposed message.

In one embodiment, message analyzer 104 may have a list of terms to beexcluded from being selected as search terms.

In one embodiment, message analyzer 104 may utilize sentiment analysisin identifying search terms and posts related to the proposed message onthe social network. For example, message analyzer 104 may identify thosesearch terms that are consistent with the attitude of user 101 expressedin the proposed message.

In step 304, message analyzer 104 searches the social network toidentify mentions (@mention) and hashtags (#) related to the identifiedsearch terms and posts. For example, in the posts directed to McCarronbeing traded, the mentions and hashtags of @cincyjungle,#bengals-nation, and #cowboys were used.

In step 305, message analyzer 104 ranks the search terms in order ofusage among the identified posts. For example, message analyzer 104 mayrank the following observed terms in order of highest usage: McCarrontraded, McCarron new team. By ranking the observed terms in order ofhighest usage, those terms that are used the most are likely to improvethe discoverability of the proposed message if utilized in the proposedmessage.

In step 306, message analyzer 104 identifies and highlights the word(s)in the proposed message to be substituted with the identified searchterms. In one embodiment, message analyzer 104 utilizes natural languageprocessing to match the word(s) used in the proposed message thatcoincides with the meaning of the most utilized search terms, such asthe highest ranked search terms. Such word(s) can be highlighted toindicate that more appropriate search terms can replace such word(s) toimprove the discoverability of the message on the social network. Forexample, in the proposed message of “Starting QB Team traded. What areyour thoughts?”, the words of “Team traded” may be highlighted sincethey coincide with the meaning of the most utilized search terms (e.g.,McCarron traded, McCarron new team).

In step 307, message analyzer 104 presents a list of search terms inorder of rank to user 101 to substitute the highlighted word(s) in theproposed message. For example, the list of the search terms may includethe search terms of “McCarron traded,” and “McCarron new team,” in orderof rank (most utilized to least utilized).

In step 308, a determination is made by message analyzer 104 as towhether it received a selection of search term(s) from the presentedlist of search terms by user 101 to modify the proposed message.

If user 101 did not select a search term from the presented list ofsearch terms to modify the proposed message, then, in step 309, messageanalyzer 104 does not modify the proposed message.

In step 310, message analyzer 104 posts the message on the socialnetwork.

If, however, message analyzer 104 received a selection of search term(s)from the presented list of search terms by user 101, then, in step 311,message analyzer 104 modifies the proposed message to replace thehighlighted word(s) with the selected search term(s).

For example, in the proposed message of “Starting QB Team traded. Whatare your thoughts?”, where the words of “Team traded” are highlighted,if user 101 selects the search term of “McCarron traded” from the listof search terms provided to user 101, then the message is modified asfollows: “Starting QB McCarron traded. What are your thoughts?”

In one embodiment, message analyzer 104 includes a type-ahead feature tomodify the message whereby if user 101 enters a character to modify themessage, message analyzer 104 auto-completes the word using the termthat highly correlates to the topic or activity of the proposed messagerelevant to the target audience. For example, message analyzer 104 usesnatural language processing to determine the topic or activity of theproposed message. For instance, message analyzer 104 uses naturallanguage processing to identify keywords (e.g., baseball, hockey,travel) to determine the topic of the proposed message. When the userenters the character(s) of “ho,” message analyzer 104 may automaticallycomplete the word “hockey” if the proposed message is directed to thesport of hockey and is relevant to the target audience (e.g., followersof a hockey team).

In one embodiment, message analyzer 104 splits the proposed message intomultiple new messages to maximize the discoverability of the message.For example, message analyzer 104 may determine that the message wouldbe more likely to be discovered and responded by shortening the lengthof the message and splitting the message into multiple messages. In oneembodiment, message analyzer 104 implements a threshold number ofcharacters in determining whether a message is to be split to maximizethe discoverability of the message.

Referring now to FIG. 3B, in conjunction with FIGS. 1-2, in step 312,message analyzer 104 presents the user with a list of mentions andhashtags used in posts related to the selected search term (e.g.,“McCarron traded”). For example, message analyzer 104 presents thefollowing list of mentions and hashtags of “@cincyjungle,”“#bengals-nation,” and “#cowboys” that are related to the selectedsearch term of “McCarron traded.” Such mentions and hashtags may be usedby user 101 to improve the discoverability of the message on the socialnetwork.

In step 313, a determination is made by message analyzer 104 as towhether it received a selection of a mention or hashtag from thepresented list of mentions and hashtags by user 101.

If message analyzer 104 did not receive a selection of a mention orhashtag from user 101, then, in step 314, message analyzer 104 does notmodify the proposed message.

In step 315, message analyzer 104 posts the message on the socialnetwork.

If, however, message analyzer 104 received a selection of a mention orhashtag from user 101, then, in step 316, message analyzer modifies theproposed message by including the selected mention or hashtag. Forinstance, referring to the above example, if user 101 selected themention/hashtag of “#bengals-nation,” then the proposed message would bemodified as follows: “Starting QB McCarron traded. What are yourthoughts? #bengals-nation”.

In this manner, the message created by user 101 has been modified toimprove the discoverability of the message on the social network byincluding such search term(s) and/or mention(s)/hashtag(s) which aremore likely to catch the attention of recipients, especially if suchsearch term(s)/mention(s)/hashtag(s) are currently trending.Furthermore, by including such search term(s) and/ormention(s)/hashtag(s), the recipients will be more appropriate. That is,user 101 will be able to reach the appropriate target audience byincluding those term(s)/and/or mention(s)/hashtag(s) that are designedto catch their attention. Furthermore, user 101 will receive moreresponses to his/her message by an appropriate target audience.

Upon modifying the proposed message as discussed in step 316, messageanalyzer 104, in step 317, posts the message on the social network.

At times, user 101 may create a message that specifically states atargeted group, such as via a mention or hashtag. A process forimproving the discoverability of such messages is discussed below inconnection with FIG. 4.

FIG. 4 is a flowchart of a method 400 for improving the discoverabilityof a message on a social network where the message includes a mention orhashtag in accordance with an embodiment of the present invention.

Referring now to FIG. 4, in conjunction with FIGS. 1-2 and 3A-3B, instep 401, a determination is made by message analyzer 104 as whether thecreation of a proposed message with a mention or hashtag by user 101 isdetected. Message analyzer 104 determines whether the creation of aproposed message with a mention or hashtag by user 101 (e.g.,“Slice-and-diced ECMA 9.0a JavaScript released to open source engineers.#engineers”) is detected in the same manner as determining whether thecreation of a proposed message is detected in step 301. For the sake ofbrevity, the details regarding the determination step will not bereiterated for the sake of brevity.

If message analyzer 104 has not detected the creation of a proposedmessage by user 101, then message analyzer 104 continues to monitor forthe creation of a proposed message with a mention or hashtag by user 101in step 401.

If, however, message analyzer 104 has detected the creation of aproposed message with a mention or hashtag by user 101, then, in step402, a determination is made by message analyzer 104 as to whether theproposed message requests a response from people or a group who arementioned or who are followers of the hashtag.

For example, in the proposed message of “Slice-and-diced ECMA 9.0aJavaScript released to open source engineers. #engineers”, messageanalyzer 104 determines whether the proposed message requests a responsefrom the followers of #engineers.

In one embodiment, message analyzer 104 utilizes natural languageprocessing to determine whether the proposed message requests a responsefrom the people or the group who are mentioned or who are followers ofthe hashtag as discussed above in connection with step 302. For the sakeof brevity, the details regarding the determination step will not bereiterated for the sake of brevity.

If the proposed message does not request a response from the people orthe group who are mentioned or who are followers of the hashtag, thenmessage analyzer 104 continues to monitor for the creation of a proposedmessage with a mention or hashtag by user 101 in step 401.

If, however, the proposed message requests a response from the people orthe group who are mentioned or who are followers of the hashtag, then,in step 403, message analyzer 104 searches the social network toidentify search terms and posts related to the proposed message used bythe people or the group who are mentioned or who are followers of thehashtag.

In one embodiment, message analyzer 104 utilizes natural languageprocessing to identify search terms and posts related to the proposedmessage used by the people or the group who are mentioned or who arefollowers of the hashtag as discussed above in connection with step 303.For example, message analyzer 104 identifies the search terms of: “ECMAadvancement,” “ruby glass,” “ruby,” as well as the post of “ECMA isterribly tough.” For the sake of brevity, the details regarding thesearching step will not be reiterated for the sake of brevity.

In step 404, message analyzer 104 ranks the search terms in order ofusage among the identified posts. For example, message analyzer 104 mayrank the following observed terms in order of highest usage: ruby, ecma,glass. By ranking the observed terms in order of highest usage, thoseterms that are used the most are likely to improve the discoverabilityof the proposed message if utilized in the proposed message. In oneembodiment, message analyzer 104 ranks the search terms in order ofusage among the identified posts as discussed above in connection withstep 305. For the sake of brevity, the details regarding the rankingstep will not be reiterated for the sake of brevity.

In step 405, message analyzer 104 identifies and highlights the word(s)in the proposed message related to the identified search terms. In oneembodiment, message analyzer 104 utilizes natural language processing tomatch word(s) used in the proposed message that coincides with themeaning of the most utilized search terms, such as the highest rankedsearch terms.

In step 406, message analyzer 104 presents a list of search terms inorder of rank to user 101 to append to the mention or hashtag in theproposed message. For example, the list of the search terms may includethe search terms of “ruby,” “ecma,” and “glass.”

In step 407, a determination is made by message analyzer 104 as towhether it received a selection of search term(s) from the presentedlist of search terms by user 101 to modify the proposed message.

If user 101 did not select a search term from the presented list ofsearch terms to modify the proposed message, then, in step 408, messageanalyzer 104 does not modify the proposed message.

In step 409, message analyzer 104 posts the message on the socialnetwork.

If, however, message analyzer 104 received a selection of search term(s)from the presented list of search terms by user 101, then, in step 410,message analyzer 104 modifies the proposed message to append theselected search term(s) to the existing mention or hashtag in theproposed message.

For instance, in the proposed message of “Slice-and-diced ECMA 9.0aJavaScript released to open source engineers. #engineers”, if user 101selects the search terms of “ruby” and “ecma,” then the message ismodified as follows: “Slice-and-diced ECMA 9.0a JavaScript released toopen source engineers. #engineers ruby ecma”.

In one embodiment, as discussed above, message analyzer 104 includes atype-ahead feature to modify the message whereby if user 101 enters acharacter to modify the message, message analyzer 104 auto-completes theword using the term that highly correlates to the topic or activity ofthe proposed message relevant to the target audience. For example,message analyzer 104 uses natural language processing to determine thetopic or activity of the proposed message. For instance, messageanalyzer 104 uses natural language processing to identify keywords(e.g., baseball, hockey, travel) to determine the topic of the proposedmessage. When the user enters the character(s) of “ho,” message analyzer104 may automatically complete the word “hockey” if the proposed messageis directed to the sport of hockey and is relevant to the targetaudience (e.g., followers of a hockey team).

In one embodiment, message analyzer 104 splits the proposed message intomultiple new messages to maximize the discoverability of the message.For example, message analyzer 104 may determine that the message wouldbe more likely to be discovered and responded by shortening the lengthof the message and splitting the message into multiple messages. In oneembodiment, message analyzer 104 implements a threshold number ofcharacters in determining whether a message is to be split to maximizethe discoverability of the message.

In step 411, message analyzer 104 posts the message on the socialnetwork.

In this manner, the message created by user 101 has been modified toimprove the discoverability of the message on the social network byappending such search term(s) to the mention or hashtag which are morelikely to catch the attention of recipients, especially if such searchterm(s) are currently trending. Furthermore, by appending such searchterm(s) to the mention or hashtag, the recipients will be moreappropriate. That is, user 101 will be able to reach the appropriatetarget audience by appending those term(s) to the mention or hashtagthat are designed to catch their attention. Furthermore, user 101 willreceive more responses to his/her message by an appropriate targetaudience.

As a result of the principles of the present invention, messages aremodified to be more discoverable on a social network. Modifying messagesin the manner discussed herein is performed in a non-conventional way.By using computing technology to modify messages, such as replacingterm(s) in a proposed message with relevant search term(s) identified ona social network or inserting a relevant mention or hashtag identifiedon the social network or appending relevant search term(s) identified onthe social network to a pre-existing mention or hashtag in the proposedmessage, the message will now be more likely to be discovered andresponded by an appropriate target audience thereby increasing thenumber of responses the author of the message will receive. Increasingthe number of responses the author of the message will receive improvesthe utilization of online social networks.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

1. A computer program product for improving discoverability of messageson a social network, the computer program product comprising one or morecomputer readable storage mediums having program code embodiedtherewith, the program code comprising programming instructions for:detecting a creation of a proposed message that requests a response froma target audience, wherein the proposed message comprises one or morewords; searching the social network to identify search terms and postsrelated to the proposed message; ranking the identified search terms inorder of usage among the identified posts; presenting a list of rankedsearch terms to a user to substitute at least one word of the one ormore words in the proposed message; modifying the proposed message byreplacing the at least one word with a respective search term from thelist of ranked search terms in response to the user selecting therespective search term; and posting the modified proposed message on thesocial network.
 2. The computer program product as recited in claim 1,wherein the program code further comprises programming instructions for:identifying and highlighting the at least one word in the proposedmessage to be substituted with the respective search term.
 3. Thecomputer program product as recited in claim 2, wherein the program codefurther comprises programming instructions for: presenting the list ofranked search terms to the user to substitute the at least onehighlighted word; and modifying the proposed message by replacing the atleast one highlighted word with the respective search term from the listof ranked search terms.
 4. The computer program product as recited inclaim 1, wherein the creation of the proposed message is detected bydetecting the one or more words being entered in a message box used forposting the proposed message on the social network.
 5. The computerprogram product as recited in claim 1, wherein the modifications of theproposed message comprise splitting the proposed message into multiplenew messages.
 6. The computer program product as recited in claim 1,wherein the program code further comprises programming instructions for:utilizing synonyms, colloquialisms and antonyms of keywords detected inthe proposed message when searching the social network to expand atleast a subset of the identified search terms and posts related to theproposed message.
 7. The computer program product as recited in claim 1,wherein the program code further comprises programming instructions for:utilizing a list of terms to be excluded from being selected as searchterms from the list of ranked search terms.
 8. The computer programproduct as recited in claim 1, wherein the program code furthercomprises programming instructions for: searching the social network toidentify only search terms and posts that occurred within a window oftime.
 9. The computer program product as recited in claim 1, wherein theprogram code further comprises programming instructions for: searchingthe social network to identify only search terms and posts that aredeemed to be most important or relevant to the target audience involvingthe proposed message.
 10. The computer program product as recited inclaim 1, wherein the proposed message is modified using an auto-completefeature.
 11. A system for improving discoverability of messages on asocial network, comprising: a memory for storing a computer program; anda hardware processor connected to the memory, wherein the hardwareprocessor is configured to execute program instructions of the computerprogram comprising: detecting a creation of a proposed message thatrequests a response from a target audience, wherein the proposed messagecomprises one or more words; searching the social network to identifysearch terms and posts related to the proposed message; ranking theidentified search terms in order of usage among the identified posts;presenting a list of ranked search terms to a user to substitute atleast one word of the one or more words in the proposed message;modifying the proposed message by replacing the at least one word with arespective search term from the list of ranked search terms in responseto the user selecting the respective search term; and posting themodified proposed message on the social network.
 12. The system asrecited in claim 11, wherein the program instructions of the computerprogram further comprise: identifying and highlighting the at least oneword in the proposed message to be substituted with the respectivesearch term.
 13. The system as recited in claim 12, wherein the programinstructions of the computer program further comprise: presenting thelist of ranked search terms to the user to substitute the at least onehighlighted word; and modifying the proposed message by replacing the atleast one highlighted word with the respective search term from the listof ranked search terms.
 14. The system as recited in claim 11, whereinthe creation of the proposed message is detected by detecting the one ormore words being entered in a message box used for posting the proposedmessage on the social network.
 15. The system as recited in claim 11,wherein the modifications of the proposed message comprise splitting theproposed message into multiple new messages.
 16. The system as recitedin claim 11, wherein the program instructions of the computer programfurther comprise: utilizing synonyms, colloquialisms and antonyms ofkeywords detected in the proposed message when searching the socialnetwork to expand at least a subset of the identified search terms andposts related to the proposed message.
 17. The system as recited inclaim 11, wherein the program instructions of the computer programfurther comprise: utilizing a list of terms to be excluded from beingselected as search terms from the list of ranked search terms.
 18. Thesystem as recited in claim 11, wherein the program instructions of thecomputer program further comprise: searching the social network toidentify only search terms and posts that occurred within a window oftime.
 19. The system as recited in claim 11, wherein the programinstructions of the computer program further comprise: searching thesocial network to identify only search terms and posts that are deemedto be most important or relevant to the target audience involving theproposed message.
 20. The system as recited in claim 11, wherein theproposed message is modified using an auto-complete feature.